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@@ -47,7 +47,7 @@ def generate_noise(max_norm, parameter, noise_multiplier, noise_type, device):
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return 0.0
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# Server side Noise
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-def apply_noise(weights, batch_size, max_norm, noise_multiplier, noise_type, device, loss_reduction="mean"):
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+def apply_noise(weights, batch_size, max_norm, noise_multiplier, noise_type, device, loss_reduction="mean", clipping=False):
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"""
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A function for applying noise to weights on the (intermediate) server side that utilizes the generate_noise function above.
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@@ -73,7 +73,15 @@ def apply_noise(weights, batch_size, max_norm, noise_multiplier, noise_type, dev
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if isinstance(weights, dict):
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weights = weights.values()
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+ if max_norm == None:
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+ max_norm = 1.0
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+
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for p in weights:
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+ if clipping:
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+ norm = torch.norm(p, p=2)
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+ div_norm = max(1, norm/max_norm)
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+ p /= div_norm
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+
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noise = generate_noise(max_norm, p, noise_multiplier, noise_type, device)
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if loss_reduction == "mean":
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noise /= batch_size
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